Intelligence platform for scheduling product preparation and delivery

ABSTRACT

A device may receive a request for a product. Based on the request, the device may determine a geographic location and delivery time for delivery of the product, and the device may identify product locations that are capable of providing the product and located near the geographic location. The device may determine, for each of the product locations and based on the product and at least one product location characteristic, a fulfillment time indicating when the product will be prepared for delivery. In addition, the device may identify at least one potential courier capable of transporting the product. Based on the fulfillment time, the delivery time, the geographic location for delivery, and at least one courier characteristic associated with the potential courier, the device may select a particular product location and a particular courier and perform an action based on the particular product location or the particular courier.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/195,111, filed Nov. 19, 2018, which is a continuation of U.S. patentapplication Ser. No. 15/836,589, filed Dec. 8, 2017 (now U.S. Pat. No.10,163,070), which are incorporated herein by reference in theirentireties.

BACKGROUND

Consumers may order and obtain products in a variety of ways. Forexample, a consumer may order and/or purchase a product by visiting aphysical retail location site where products are stored and/or sold.Alternatively, a consumer may order and/or purchase a product online, byphone, by mail, or the like, for delivery of the product to the consumervia a carrier, such as a postal service.

SUMMARY

According to some implementations, a device may comprise: one or morememories; and one or more processors, communicatively coupled to the oneor more memories, to: receive, from a first device, a request for aproduct; determine, based on the request, a geographic location fordelivery of the product, and a delivery time for delivery of theproduct; identify, based on the request, a plurality of productlocations that are located in a geographic region associated with thegeographic location, each of the plurality of product locations being alocation capable of providing the product; determine, for each of theplurality of product locations and based on the product and at least oneproduct location characteristic, a fulfillment time, the fulfillmenttime indicating a time at which the product will be at the productlocation and prepared for delivery; identify, for each of the pluralityof product locations, at least one potential courier, each potentialcourier being capable of transporting the product from the productlocation to the geographic location; select, based on the fulfillmenttime, the delivery time, the geographic location for delivery, and atleast one courier characteristic associated with the at least onepotential courier, a particular product location of the plurality ofproduct locations and a particular courier from the at least onepotential courier; and perform an action based on the particular productlocation or the particular courier.

According to some implementations, a non-transitory computer-readablemedium may store instructions, the instructions comprising: one or moreinstructions that, when executed by one or more processors, cause theone or more processors to: receive, from a first device, a request for aproduct, the request including: information identifying a geographiclocation for delivery of the product, and information identifying adelivery time for delivery of the product; identify, based on therequest, a plurality of second devices, each second device, of theplurality of second devices, being in a geographic region associatedwith the geographic location, each second device, of the plurality ofsecond devices, being associated with a location capable of providingthe product; determine, for each second device, of the plurality ofsecond devices, and based on at least one product locationcharacteristic, a fulfillment time, the fulfillment time indicating atime at which the product will be prepared for delivery from thelocation for the second device; select, based on the fulfillment time,the delivery time, and the geographic location for delivery, aparticular location of a particular second device of the plurality ofsecond devices; and perform an action based on the particular location.

According to some implementations, a method may comprise: receiving, bya first device and from a second device, a request for a product;determining, by the first device and based on the request, a geographiclocation for delivery of the product, and a delivery time for deliveryof the product; identifying, by the first device and based on therequest, a plurality of product locations that are located in ageographic region associated with the geographic location, each of theplurality of product locations being a location capable of providing theproduct; determining, by the first device, for each of the plurality ofproduct locations, and based on the product and at least one productlocation characteristic, a fulfillment time, the fulfillment timeindicating a time at which the product will be at the product locationand prepared for delivery; identifying, by the first device and for eachof the plurality of product locations, at least one potential courier,each potential courier being capable of transporting the product fromthe product location to the geographic location; providing, by the firstdevice and for each of the plurality of product locations, a schedulingmodel with one of the at least one product location characteristics andat least one courier characteristic associated with one of the at leastone potential courier, the scheduling model having been trained toproduce, as output, an estimated completion time associated withdelivery of the product to the geographic location for delivery; andperforming, by the first device, an action based on at least oneestimated completion time obtained from the scheduling model.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1B are diagrams of an overview of an example implementationdescribed herein;

FIG. 2 is a diagram of an example environment in which systems and/ormethods, described herein, may be implemented;

FIG. 3 is a diagram of example components of one or more devices of FIG.2 ; and

FIG. 4 is a flow chart of an example process for scheduling productpreparation and delivery.

DETAILED DESCRIPTION

The following detailed description of example implementations refers tothe accompanying drawings. The same reference numbers in differentdrawings may identify the same or similar elements.

A consumer may receive products via delivery, such as by a courier.Although the consumer may wish to receive the product by a desired timeor within a desired time period, product orders are generally processedin an order that the product orders are received, and are generally sentout when a carrier is available or scheduled to make pick-ups anddeliveries. As such, it may be difficult for a consumer to specify atime window for delivery in the near future, such as within hours, or aspecific time window within days, weeks, etc. of the order or purchase.

Some implementations, described herein, may provide a schedulingplatform that gathers data from product location devices (e.g., deviceslocated at area locations that house a product), from courier devices(e.g., devices associated with independent contractors, drones,carriers, or the like), and/or from third party devices (e.g., devicesthat provide traffic data, weather data, or the like). Using the datagathered, the scheduling platform may schedule delivery of a product toa user specified location within a relatively short window of time(e.g., within a 2 hour window, starting as early as within 2 hours ofthe product being ordered).

In this way, the scheduling platform may provide an improved userexperience. For example, the scheduling platform may provide fasterdelivery of the product. As another example, the scheduling platform mayprovide on-demand delivery of the product (e.g., delivery when the userwants the delivery, and delivery scheduled within a specific futurewindow of time). In some implementations, the scheduling platform mayallow scheduling of hundreds, thousands, millions, etc., of orders fromhundreds thousands, millions, etc., of users.

Furthermore, the scheduling platform may provide situational awareness(e.g., incoming orders, delivery time, weather, traffic, etc.) toproduct location devices and/or courier devices, to enable the productlocation devices and/or courier devices to present relevant informationto entities that prepare and/or deliver the products.

Additionally, the scheduling platform may use a selective process thatidentifies devices capable of timely and efficient order processing.This may reduce resource usage of some devices by obviating the need fororders to wait in a queue at the scheduling platform, product locationdevices, and/or courier devices, which may conserve processing, storage,and network resources. In addition, by selectively sending orders todevices that are associated with entities capable of fulfilling theorders within the user specified time window, delivery bottlenecks maybe avoided, and costs associated with delivering products may be reduced(e.g., by selecting a delivery method with a lower cost than anotherdelivery method). In this way, selection of a product location deviceand/or a courier device may be made in a way that is more efficient thanother selection methods in that it may lead to faster order fulfillment,less hardware resource consumption, and lower costs for an entity thatprepares and provides products to users.

FIGS. 1A-1B are diagrams of an overview of an example implementation 100described herein. As shown in FIG. 1A, example implementation 100 mayinclude a user device, a scheduling platform, one or more productlocation device(s), one or more courier device(s), and one or more thirdparty device(s). In some implementations, the scheduling platform mayinclude a cloud computing platform, one or more server devices, or thelike. The scheduling platform may be associated with an entity thatprovides products and/or services to users, such as a user associatedwith the user device. As one example, the scheduling platform may beassociated with a bank that desires to offer quick delivery of bankingproducts (e.g., credit cards, debit cards, cash, cashier's checks,etc.).

In some implementations, the product location devices may includedevices located at a physical location that may have products available,such as a warehouse, a retail location, product storage locker, or thelike. In some implementations, the courier device(s) may include adevice associated with a courier (e.g., an entity capable of deliveringa product, such as an independent contractor-based delivery person, adelivery drone, a commercial carrier, or the like), such as a dronecontrol device, a smart phone, a personal computer, a server computer,or the like. In some implementations, the third party devices mayinclude other user devices, server devices, or the like, which arecapable of providing relevant information to the scheduling platform.

As shown in FIG. 1A, and by reference number 105, the user device maysend, to the scheduling platform, a request for a product. For example,a user of the user device may send a request for a cashier's check tothe scheduling platform (e.g., using a banking application operating onthe user device). In some implementations, data associated with therequest may indicate the product, the location to which the productshould be delivered (e.g., an address at which the user is or will belocated), and a time at which the product is to be delivered (e.g., atime during which someone will be at home to receive the product).

As further shown in FIG. 1A, and by reference number 110, the schedulingplatform may send a request to the product location device(s), such asdevices associated with a product location that may have the product instock and/or may be near the delivery location. As shown by referencenumber 115, the scheduling platform may receive product locationcharacteristics, such as data indicating which products are in stock atthe associated location, which entities are capable of preparingparticular products (e.g., for specialized products that need someonespecific, like a cashier's check), schedules for those entities, or thelike.

As further shown in FIG. 1A, and by reference number 120, a schedulingplatform may send, to the third party device(s), a request forinformation that may affect timing of a delivery. The request may beassociated with information that the third party devices(s) can use toobtain and/or determine such information, such as a product location, adelivery time and/or a delivery location. As shown by reference number125, the scheduling platform may receive, from the third party devices,the information that may affect timing of a delivery, such as trafficdata associated with traffic conditions (e.g., current or projectedtraffic conditions), and/or weather data associated with weatherconditions (e.g., current or projected weather conditions), or the like.

As further shown in FIG. 1A, and by reference number 130, the schedulingplatform may send, to the courier device(s), a request associated withdata specifying the delivery location and the delivery time. In someimplementations, the request may also be associated with productlocation information specifying the product location(s), as a couriermay pick up the product at a product location. As shown by referencenumber 135, the scheduling platform may receive courier characteristicsfrom the courier devices. For example, the courier characteristics mayinclude a cost associated with the courier, a range associated with thecourier, availability for the courier, traffic conditions associatedwith the courier, insurance characteristics associated with the courier,a language spoken by the courier, information relating to the quantityof on-time deliveries that the courier has made, and/or the like.

As shown in FIG. 1B, the data provided to the scheduling platform in theexample implementation 100 of FIG. 1A may be used to determine aparticular courier device and a particular product location device(e.g., based on the data received by the scheduling platform). Exampleimplementation 150 may include the user device, the scheduling platform,a particular product location device, and a particular courier device.As shown by reference number 155, the scheduling platform may use theinformation received from the product location device(s), the thirdparty device(s), and/or the courier device(s) to determine a particularcourier and a particular product location. The determination may be madein a variety of ways, which is discussed in further detail below.

As further shown in FIG. 1B, and by reference number 160, the schedulingplatform may send selection data to the particular product locationdevice. The selection data may be sent based on the selection of theparticular product location device (e.g., in response to selection ofthe particular product location device). The selection data may specify,for example, the product and a fulfillment time (e.g., a time that theproduct needs to be prepared for pickup by a courier associated with theparticular courier device). The selection data may, in someimplementations, include or be associated with other data designed toenable the product to be prepared by the fulfillment time.

As further shown in FIG. 1B, and by reference number 165, the schedulingplatform may send selection data to the particular courier device. Theselection data may be sent based on the selection of the particularcourier device (e.g., in response to selection of the particular productlocation device). The selection data may include, for example, theproduct location, delivery location, and delivery time (e.g., enablingthe carrier to pick up the product from the product location and deliverit to the user by or within the delivery time). As further shown in FIG.1B, and by reference number 170, the scheduling platform may send adelivery confirmation to the user device, e.g., in a manner designed toconfirm when and/or how the product will be delivered.

In this way, the scheduling platform may provide an improved userexperience. For example, the scheduling platform may provide quickdelivery of the product. As another example, the scheduling platform mayprovide on-demand delivery of the product (e.g., delivery when the userwants the delivery, and delivery scheduled within a specific futurewindow of time). In some implementations, the scheduling platform mayallow scheduling of hundreds, thousands, millions, etc., of orders fromhundreds thousands, millions, etc., of users.

Furthermore, the scheduling platform may provide situational awareness(e.g., incoming orders, delivery time, weather, traffic, etc.) toproduct location devices and/or courier devices, to enable the productlocation devices and/or courier devices to present relevant informationto entities that prepare and/or deliver the products.

Additionally, the scheduling platform may use a selective process thatidentifies devices capable of timely and efficient order processing.This may reduce resource usage of some devices by obviating the need fororders to wait in a queue at the scheduling platform, product locationdevices, and/or courier devices, which may conserve processing, storage,and network resources. In addition, by selectively sending orders todevices that are associated with entities capable of fulfilling theorders within the user specified time window, delivery bottlenecks maybe avoided, and costs associated with delivering products may be reduced(e.g., by selecting a delivery method with a lower cost than anotherdelivery method). In this way, selection of a product location deviceand/or a courier device may be made in a way that is more efficient thanother selection methods in that it may lead to faster order fulfillment,less hardware resource consumption, and lower costs for an entity thatprepares and provides products to users.

As indicated above, FIGS. 1A-1B are provided merely as an example. Otherexamples are possible and may differ from what was described with regardto FIGS. 1A-1B.

FIG. 2 is a diagram of an example environment 200 in which systemsand/or methods, described herein, may be implemented. As shown in FIG. 2, environment 200 may include user device 210, product locationdevice(s) 220, scheduling platform 225 hosted within a cloud computingenvironment 230, courier device(s) 240, and third party device(s) 250.Devices of environment 200 may interconnect via wired connections,wireless connections, or a combination of wired and wirelessconnections.

User device 210 includes one or more devices capable of receiving,generating, storing, processing, and/or providing information associatedwith requests for products. For example, user device 210 may include acommunication and/or computing device, such as a mobile phone (e.g., asmart phone, a radiotelephone, etc.), a laptop computer, a tabletcomputer, a handheld computer, a gaming device, a wearable communicationdevice (e.g., a smart wristwatch, a pair of smart eyeglasses, etc.), ora similar type of device. In some implementations, user device 210 mayinclude one or more applications for ordering products, such as a webbrowsing application for ordering products from a website, a schedulingplatform application associated with scheduling platform 225 forordering products from an entity associated with scheduling platform225, or the like.

Product location device(s) 220 include one or more devices capable ofreceiving, generating, storing, processing, and/or providing informationassociated with products, including product availability and preparationtimes. For example, product location device 220 may include acommunication and/or computing device, such as a mobile phone (e.g., asmart phone, a radiotelephone, etc.), a laptop computer, a tabletcomputer, a handheld computer, a gaming device, a wearable communicationdevice (e.g., a smart wristwatch, a pair of smart eyeglasses, etc.), ora similar type of device. Product location device 220 may be associatedwith a product location (e.g., a location that houses products, which anentity associated with the product location can prepare for delivery toa user). In some implementations, product location device 220 may beassociated with one or more entities associated with a product location(e.g., product location device 220 may be associated with a particularperson at a product location, a particular piece of equipment at aproduct location, or the like). By way of example, product locationdevice 220 may be a wearable communication device worn by a personcapable of preparing a particular product or products for delivery. Asanother example, product location device 220 may be a computing deviceconnected to a device for preparing products, such as a cashier's checkprinter capable of preparing cashier's checks for delivery.

Scheduling platform 225 includes one or more devices capable ofreceiving, generating, storing, processing, and/or providing informationassociated with scheduling the preparation and delivery of products.While the example environment 200 indicates that scheduling platform 225is implemented in a cloud computing environment 230, in someimplementations, scheduling platform 225 may be implemented by one ormore other types of devices as well, such as a server computer, laptopcomputer, tablet computer, handheld computer, or the like. Schedulingplatform 225 is capable of using data provided by user device 210,product location device(s) 220, courier device(s) 240, and/or thirdparty device(s) 250 to schedule the preparation and delivery of aproduct. Scheduling platform 225 may, in some implementations, includeor otherwise have access to other resources to facilitate schedulingpreparation and delivery of products, including resources for generatingmodels via machine learning, resources for storing historicalpreparation and delivery data, or the like.

Cloud computing environment 230 includes an environment that deliverscomputing as a service, whereby shared resources, services, etc. may beprovided to schedule preparation and delivery of products. Cloudcomputing environment 230 may provide computation, software, dataaccess, storage, and/or other services that do not require end-userknowledge of a physical location and configuration of a system and/or adevice that delivers the services. As shown, cloud computing environment230 may include scheduling platform 225 and computing resource 235.

Computing resource 235 includes one or more personal computers,workstation computers, server devices, or another type of computationand/or communication device. In some implementations, computing resource235 may host scheduling platform 225. The cloud resources may includecompute instances executing in computing resource 235, storage devicesprovided in computing resource 235, data transfer devices provided bycomputing resource 235, etc. In some implementations, computing resource235 may communicate with other computing resources 235 via wiredconnections, wireless connections, or a combination of wired andwireless connections.

As further shown in FIG. 2 , computing resource 235 may include a groupof cloud resources, such as one or more applications (“APPs”) 235-1, oneor more virtual machines (“VMs”) 235-2, virtualized storage (“VSs”)235-3, one or more hypervisors (“HYPs”) 235-4, or the like.

Application 235-1 includes one or more software applications that may beprovided to or accessed by user device 210. Application 235-1 mayeliminate a need to install and execute the software applications onuser device 210. For example, application 235-1 may include softwareassociated with scheduling platform 225 and/or any other softwarecapable of being provided via cloud computing environment 230. In someimplementations, one application 235-1 may send/receive informationto/from one or more other applications 235-1, via virtual machine 235-2.

Virtual machine 235-2 includes a software implementation of a machine(e.g., a computer) that executes programs like a physical machine.Virtual machine 235-2 may be either a system virtual machine or aprocess virtual machine, depending upon use and degree of correspondenceto any real machine by virtual machine 235-2. A system virtual machinemay provide a complete system platform that supports execution of acomplete operating system (“OS”). A process virtual machine may executea single program, and may support a single process. In someimplementations, virtual machine 235-2 may execute on behalf of a user(e.g., user device 210), and may manage infrastructure of cloudcomputing environment 230, such as data management, synchronization, orlong-duration data transfers.

Virtualized storage 235-3 includes one or more storage systems and/orone or more devices that use virtualization techniques within thestorage systems or devices of computing resource 235. In someimplementations, within the context of a storage system, types ofvirtualizations may include block virtualization and filevirtualization. Block virtualization may refer to abstraction (orseparation) of logical storage from physical storage so that the storagesystem may be accessed without regard to physical storage orheterogeneous structure. The separation may permit administrators of thestorage system flexibility in how the administrators manage storage forend users. File virtualization may eliminate dependencies between dataaccessed at a file level and a location where files are physicallystored. This may enable optimization of storage use, serverconsolidation, and/or performance of non-disruptive file migrations.

Hypervisor 235-4 provides hardware virtualization techniques that allowmultiple operating systems (e.g., “guest operating systems”) to executeconcurrently on a host computer, such as computing resource 235.Hypervisor 235-4 may present a virtual operating platform to the guestoperating systems, and may manage the execution of the guest operatingsystems. Multiple instances of a variety of operating systems may sharevirtualized hardware resources.

Courier device(s) 240 include one or more one or more devices capable ofreceiving, generating, storing, processing, and/or providing informationassociated with products, including product pickup and delivery times.For example, courier device 240 may include a communication and/orcomputing device, such as a mobile phone (e.g., a smart phone, aradiotelephone, etc.), a laptop computer, a tablet computer, a handheldcomputer, a gaming device, a wearable communication device (e.g., asmart wristwatch, a pair of smart eyeglasses, etc.), or a similar typeof device. Courier device 240 may be associated with a courier (e.g., anentity capable of picking up a product from a product location anddelivering the product to a delivery location). In some implementations,courier device 240 may be associated with one or more entities capableof delivering a product (e.g., courier device 240 may be associated witha drone fleet management device, courier service server device, carrierserver device, or the like). By way of example, courier device 240 maybe a smart phone owned by a person capable of picking up a product froma product location and delivering that product to a delivery location.As another example, courier device 240 may be a drone fleet managementdevice capable of scheduling and deploying drones to pick up and/ordeliver products.

Third party device(s) 250 include one or more one or more devicescapable of receiving, generating, storing, processing, and/or providinginformation associated with scheduling preparation and delivery ofproducts. For example, third party device 250 may include acommunication and/or computing device, such as a server computer, mobilephone (e.g., a smart phone, a radiotelephone, etc.), a laptop computer,a tablet computer, a handheld computer, a gaming device, a wearablecommunication device (e.g., a smart wristwatch, a pair of smarteyeglasses, etc.), or a similar type of device. Third party device 250may be capable of providing a variety of information upon request. Forexample, third party device 250 may be associated with a weather server,which may provide weather-related information (e.g., current conditions,forecasted conditions, or the like) for particular geographic areas. Asanother example, third party device 250 may be associated with a trafficserver, which may provide traffic-related information (e.g., automobiletraffic, air traffic, or the like) for particular geographic areasand/or routes.

Network 260 includes one or more wired and/or wireless networks. Forexample, network 260 may include a cellular network (e.g., a long-termevolution (LTE) network, a code division multiple access (CDMA) network,a 3G network, a 4G network, a 5G network, another type of nextgeneration network, etc.), a public land mobile network (PLMN), a localarea network (LAN), a wide area network (WAN), a metropolitan areanetwork (MAN), a telephone network (e.g., the Public Switched TelephoneNetwork (PSTN)), a private network, an ad hoc network, an intranet, theInternet, a fiber optic-based network, a cloud computing network, or thelike, and/or a combination of these or other types of networks.

The number and arrangement of devices and networks shown in FIG. 2 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 2 . Furthermore, two or more devices shown in FIG. 2 maybe implemented within a single device, or a single device shown in FIG.2 may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) ofenvironment 200 may perform one or more functions described as beingperformed by another set of devices of environment 200.

FIG. 3 is a diagram of example components of a device 300. Device 300may correspond to user device 210, product location device 220,scheduling platform 225 hosted within a cloud computing environment 230,courier device 240, and/or third party device 250. In someimplementations, user device 210, product location device 220,scheduling platform 225 hosted within a cloud computing environment 230,courier device 240, and/or third party device 250 may include one ormore devices 300 and/or one or more components of device 300. As shownin FIG. 3 , device 300 may include a bus 310, a processor 320, a memory330, a storage component 340, an input component 350, an outputcomponent 360, and a communication interface 370.

Bus 310 includes a component that permits communication among thecomponents of device 300. Processor 320 is implemented in hardware,firmware, or a combination of hardware and software. Processor 320 is acentral processing unit (CPU), a graphics processing unit (GPU), anaccelerated processing unit (APU), a microprocessor, a microcontroller,a digital signal processor (DSP), a field-programmable gate array(FPGA), an application-specific integrated circuit (ASIC), or anothertype of processing component. In some implementations, processor 320includes one or more processors capable of being programmed to perform afunction. Memory 330 includes a random access memory (RAM), a read onlymemory (ROM), and/or another type of dynamic or static storage device(e.g., a flash memory, a magnetic memory, and/or an optical memory) thatstores information and/or instructions for use by processor 320.

Storage component 340 stores information and/or software related to theoperation and use of device 300. For example, storage component 340 mayinclude a hard disk (e.g., a magnetic disk, an optical disk, amagneto-optic disk, and/or a solid state disk), a compact disc (CD), adigital versatile disc (DVD), a floppy disk, a cartridge, a magnetictape, and/or another type of non-transitory computer-readable medium,along with a corresponding drive.

Input component 350 includes a component that permits device 300 toreceive information, such as via user input (e.g., a touch screendisplay, a keyboard, a keypad, a mouse, a button, a switch, and/or amicrophone). Additionally, or alternatively, input component 350 mayinclude a sensor for sensing information (e.g., a global positioningsystem (GPS) component, an accelerometer, a gyroscope, and/or anactuator). Output component 360 includes a component that providesoutput information from device 300 (e.g., a display, a speaker, and/orone or more light-emitting diodes (LEDs)).

Communication interface 370 includes a transceiver-like component (e.g.,a transceiver and/or a separate receiver and transmitter) that enablesdevice 300 to communicate with other devices, such as via a wiredconnection, a wireless connection, or a combination of wired andwireless connections. Communication interface 370 may permit device 300to receive information from another device and/or provide information toanother device. For example, communication interface 370 may include anEthernet interface, an optical interface, a coaxial interface, aninfrared interface, a radio frequency (RF) interface, a universal serialbus (USB) interface, a Wi-Fi interface, a cellular network interface, orthe like.

Device 300 may perform one or more processes described herein. Device300 may perform these processes based on processor 320 executingsoftware instructions stored by a non-transitory computer-readablemedium, such as memory 330 and/or storage component 340. Acomputer-readable medium is defined herein as a non-transitory memorydevice. A memory device includes memory space within a single physicalstorage device or memory space spread across multiple physical storagedevices.

Software instructions may be read into memory 330 and/or storagecomponent 340 from another computer-readable medium or from anotherdevice via communication interface 370. When executed, softwareinstructions stored in memory 330 and/or storage component 340 may causeprocessor 320 to perform one or more processes described herein.Additionally, or alternatively, hardwired circuitry may be used in placeof or in combination with software instructions to perform one or moreprocesses described herein. Thus, implementations described herein arenot limited to any specific combination of hardware circuitry andsoftware.

The number and arrangement of components shown in FIG. 3 are provided asan example. In practice, device 300 may include additional components,fewer components, different components, or differently arrangedcomponents than those shown in FIG. 3 . Additionally, or alternatively,a set of components (e.g., one or more components) of device 300 mayperform one or more functions described as being performed by anotherset of components of device 300.

FIG. 4 is a flow chart of an example process 400 for scheduling productpreparation and delivery. In some implementations, one or more processblocks of FIG. 4 may be performed by scheduling platform 225 hostedwithin a cloud computing environment 230. In some implementations, oneor more process blocks of FIG. 4 may be performed by another device or agroup of devices separate from or including scheduling platform 225,such as user device 210, product location device(s) 220, courierdevice(s) 240, and/or third party device(s) 250. While portions of thefollowing description use examples related to the delivery of afinancial product, implementations described herein are equallyapplicable to other types of product deliveries, such as, fooddeliveries, electronics deliveries, clothing deliveries, deliveries ofservices personnel, or the like.

As shown in FIG. 4 , process 400 may include receiving a request for aproduct (block 410). For example, scheduling platform 225 may receive arequest for a product from user device 210, e.g., via network 260. Userdevice 210 may send the request in a variety of ways, e.g., using anapplication operating on user device 210, including a communicationsapplication, ordering application associated with scheduling platform225, web browsing application, or the like. In some implementations, therequest may originate from scheduling platform 225 automatically, e.g.,in response to user device 210 communicating preferences for periodicordering of a product and/or product ordering in response to occurrenceof a particular event.

In some implementations, the product may be a financial product, such asa credit card, a debit card, cash, a cashier's check, or the like. Insome implementations, the request may indicate or be associated withdata identifying the product, a delivery location to which the productis to be delivered, and/or a time at which the product is to bedelivered. For example, the request may be sent with GPS dataidentifying a location of user device 210, and the location identifiedby the GPS data may be the delivery location. As another example, a userof user device 210 may provide input indicating a delivery location,such as a street address. The delivery time may be, for example, aspecific date/time or a window of time on a particular date, and in someimplementations the delivery time may be immediate (e.g., user isrequesting the product be delivered as soon as possible).

In this way, scheduling platform 225 may receive a request for aproduct, enabling scheduling platform 225 to determine a geographiclocation for delivery of the product and a delivery time for delivery ofthe product.

As further shown in FIG. 4 , process 400 may include determining ageographic location for delivery of the product, and a delivery time fordelivery of the product (block 420). For example, scheduling platform225 may determine a geographic location for delivery of the product(e.g., a delivery location), and scheduling platform 225 may determine adelivery time for delivery of the product. The delivery location and thedelivery time may be determined, for example, based on data associatedwith the request provided by user device 210.

As noted above, in some implementations, scheduling platform 225 maydetermine the delivery location based on geo-location information (e.g.,GPS data) that is provided by user device 210 and/or manually input bythe user. Additionally, or alternatively, scheduling platform 225 maydetermine the delivery location based on address information, such as ahome address of a user of user device 210 (e.g., stored on user device210, previously obtained and stored by scheduling platform 225, or thelike).

In some implementations, the delivery location may be non-static, and/ordynamically updated (e.g., in a situation where the delivery is to bemade to a location associated with a moving user device 210). Forexample, user device 210 sensor data (e.g., GPS, Wi-Fi, Bluetooth,camera, or the like) may be periodically provided to scheduling platform225, enabling scheduling platform 225 to determine where user device 210is located during the product preparation and delivery process. This mayenable scheduling platform 225 to more accurately enable delivery of theproduct to a location of user device 210. In some implementations,scheduling platform 225 may use user device 210 sensor data to determinea speed and direction of travel for user device 210 (e.g., in a mannerdesigned to predict where user device 210 will be located).Additionally, or alternatively, scheduling platform 225 may notify userdevice 210 based on the sensor data (e.g., by providing user device 210with a prompt regarding delivery to user device 210 or to a specificlocation of the user's choosing). Notifications may be sent to userdevice 210, for example, to confirm a delivery location (e.g., for everydelivery, or based on particular events, such as when schedulingplatform 225 lacks confidence in location prediction based on, forexample, user device 210 speed meeting a threshold.

In some implementations, scheduling platform 225 may determine thedelivery time based on a time specified by a user of user device 210.For example, the user may specify a particular time, such as a targettime, a latest possible time, an earliest possible time, or the like. Asanother example, the user may specify a window of time, such as betweenan earliest possible time and a latest possible time. As anotherexample, the user may specify guidance, a rule, a priority, or the like,such as “as soon as possible”. In some implementations, schedulingplatform 225 may provide, to a device (e.g., user device 210), dataindicating available delivery times, and may receive, from the device, aselection from the available delivery times. In this situation,scheduling platform 225 may determine the delivery time based on theselection from the available delivery times.

In this way, scheduling platform 225 may determine a geographic locationfor delivery of the product and a delivery time for delivery of theproduct, enabling scheduling platform 225 to identify product locationsthat are located in a geographic region associated with the geographiclocation.

As shown in FIG. 4 , process 400 may include identifying a productlocation based on the request (block 430). For example, schedulingplatform 225 may identify product locations that are located in ageographic region associated with the delivery location. Productlocations are locations where products may be housed, such as a retaillocation, warehouse location, storage locker location, or the like.

In some implementations, scheduling platform 225 may identify productlocations that may have (or will have) the requested product. Forexample, scheduling platform 225 may identify product locations thathave the product based on inventory data available to schedulingplatform 225, which may include product distribution data that indicateswhen a product location is to receive products. In some implementations,scheduling platform 225 may identify product locations based onrequesting information, such as inventory data and/or productdistribution data, from product location devices. Additionally, oralternatively, scheduling platform 225 may identify product locationsbased on information, such as inventory data and/or product distributiondata, previously stored by or otherwise accessible to schedulingplatform 225. In some implementations, a product location may be mobile(e.g., a mobile retail location or mobile product storage location). Inthis situation, scheduling platform 225 may identify product locationsbased on sensor data associated with product location devices 220. Forexample, based on GPS, Wi-Fi, Bluetooth, or camera data from a productlocation device 220, scheduling platform may determine the location ofthe corresponding product location.

In some implementations, scheduling platform 225 may identify productlocations within a geographic region based on a threshold distanceassociated with the product location. For example, the thresholddistance for the product location may be based on a range characteristicassociated with the product location and/or a range characteristic of atleast one potential courier associated with the product location. By wayof example, a particular product location may be associated withmultiple potential couriers (e.g., entities capable of delivering aproduct from the particular product location). In some situations, thepotential couriers may be associated with a range characteristic (e.g.,a maximum delivery range from the product location), and schedulingplatform 225 may use the range characteristics to determine a thresholddistance for the particular product location. For example, schedulingplatform 225 may use, as the threshold distance associated with theparticular product location, a mean, median, or maximum range from thepotential couriers associated with the particular product location. Asanother example, the threshold distance may be predetermined for aproduct location or product locations.

In some implementations, scheduling platform 225 may identify a productlocation that includes a product preparing location associated with oneor more entities capable of preparing the product for delivery. Aproduct preparing location may be, for example, a retail location havingequipment and/or people that are capable of preparing a product. Forexample, a bank branch location may include equipment for printing acashier's check and personnel capable of authorizing the issuance of acashier's check and packaging the cashier's check in an appropriatemanner for delivery. Additionally, or alternatively, scheduling platform225 may identify a product location that includes a storage locationstoring the product. For example, a storage location may include astorage locker or warehouse location that houses products which, in someimplementations, may be pre-packaged for delivery. In this situation,the product may have been prepared for delivery prior to receipt of therequest for the product and left at the storage location for laterpickup and delivery by a courier.

In this way, scheduling platform 225 may identify product locations thatare located in a geographic region associated with the deliverylocation, enabling scheduling platform 225 to determine a fulfillmenttime for each of the product locations.

As shown in FIG. 4 , process 400 may include determining, for each ofthe product locations, a fulfillment time (block 440). For example,scheduling platform 225 may determine, for each of the productlocations, a fulfillment time. In some implementations, the fulfillmenttime may indicate a time at which the product will be at the productlocation and prepared for delivery. For example, the fulfillment timemay be based on the amount of time required for the product to beidentified, prepared, generated, retrieved, reviewed, approved,packaged, or the like.

In some implementations, scheduling platform 225 may determine thefulfillment time based on product location characteristics. The productlocation characteristics may specify a variety of information for aparticular product location, such as data regarding entities capable ofpreparing products for delivery, data regarding the availability of theentities, data indicating the products available at the particularproduct location, or the like. For example, a product locationcharacteristic may include data indicating one or more qualified productproviders that are associated with the product location. Each qualifiedproduct provider may include an entity capable of preparing, at theproduct location, the product for delivery. For example, a printingdevice, packaging device, and an employee may each be a qualifiedproduct provider of one or more different types of products. Anotherexample product location characteristic may include data indicatingavailability for the qualified product providers at the productlocation. For example, scheduling platform 225 may obtain or otherwisehave access to schedules, work queues, or the like, which are associatedwith the qualified product providers at a particular product location.As another example, a product location characteristic may specify, for aparticular product location, data indicating products available at theproduct location (e.g., product inventory data, which may include futureinventory and/or inventory forecasts).

In some implementations, scheduling platform 225 may receive input froma proximity detection device to determine one or more product locationcharacteristics, such as the availability of an entity capable ofpreparing products for delivery at a particular product location. Forexample, a product location may be associated with a proximity detectiondevice (e.g., a Wi-Fi device, Bluetooth device, proximity sensor, or thelike), which may detect, and in some implementations identify, anindividual that enters within range of the proximity detection device.For example, an individual may use a wearable device (e.g., a type ofproduct location device 220), which is equipped with a Bluetoothcommunications component, which enables a Bluetooth proximity detectiondevice to identify and determine when the wearable device (and theindividual wearing it) is within range. The proximity detection devicemay provide scheduling platform 225 with data indicating theavailability of an individual or individuals based on the detection ofone or more individuals within range. Using the foregoing information,scheduling platform 225 may determine whether an individual is availableto prepare a particular product.

Scheduling platform 225 may use one or more of the product locationcharacteristics to determine the fulfillment time in a variety of ways.Using the cashier's check example, scheduling platform 225 may obtain,from product location device 220 associated with a bank branch, theschedule or availability of one or more employees capable of authorizinga cashier's check, data indicating the availability of blank cashier'schecks, and data indicating the availability of a printing device forprinting the cashier's check. Using the foregoing information,scheduling platform 225 may determine the fulfillment time.

In some implementations, scheduling platform 225 may have access toprevious fulfillment times and/or predetermined fulfillment timesassociated with a product location and/or product locationcharacteristics. In this situation, the previous fulfillment timesand/or predetermined fulfillment times may be used to determine thefulfillment time for preparing a product for delivery. By way ofexample, scheduling platform 225 may have access to historical data (or,in some implementations, a predetermined fulfillment time) indicatingthat a cashier's check takes thirty minutes to prepare for delivery. Inthis situation, the fulfillment time may be determined to be thirtyminutes. In some implementations, scheduling platform 225 may use amachine learning model to determine the fulfillment time. For example, amodel may be trained, using previous product orders, fulfillment times,and product location characteristics, to provide an estimatedfulfillment time. In this situation, scheduling platform 225 mayprovide, as input to the model, data indicating one or more productlocation characteristics and receive, from the model, an estimatedfulfillment time.

In this way, scheduling platform 225 may determine a fulfillment timefor each of the product locations, enabling scheduling platform 225 toidentify at least one potential courier for each of the productlocations.

As shown in FIG. 4 , process 400 may include identifying, for each ofthe product locations, at least one potential courier (block 450). Forexample, scheduling platform 225 may identify, for each of the productlocations, at least one potential courier. In some implementations, eachpotential courier may include an entity capable of transporting theproduct from the product location to the delivery location. For example,a potential courier may be an independent contractor based deliveryperson, a drone, a commercial carrier, or the like.

In some implementations, scheduling platform 225 may identify at leastone potential courier based on obtaining courier characteristics. Forexample, courier characteristics may include data indicating a costassociated with a courier, data indicating a range associated with acourier, data indicating availability for a courier, data indicatingtraffic conditions associated with a courier, data indicating a languageor languages spoken by the courier, data relating to previous deliveriesby the courier, data indicating insurance characteristics associatedwith a courier, and/or the like. Scheduling platform 225 may obtaincourier characteristics in a variety of ways. For example, couriercharacteristics may be stored by or otherwise accessible to schedulingplatform 225, courier characteristics may be requested from a predefinedlist of couriers, or scheduling platform 225 may broadcast, in ageographic region near the product location and/or delivery location, arequest for courier characteristics.

In some implementations, scheduling platform 225 may identify apotential courier based on the range associated with the potentialcourier (e.g., a courier may be identified as a potential courier if itis capable of picking up a product from the product location anddelivering it to the delivery location). In some implementations,scheduling platform 225 may identify a potential courier based on dataindicating availability for the potential courier (e.g., a courier maynot be a potential courier if the courier is otherwise engaged orotherwise unable to deliver a product within the requested time window).In some implementations, scheduling platform 225 may identify apotential courier based on an insurance characteristic, or insurancepolicy, associated with the potential courier (e.g., for some products,scheduling platform 225 may require a particular type of insurance for acourier to be eligible to be a potential courier). As noted above, othercourier characteristics (such as the cost of a courier or trafficconditions on a delivery route) may be used, alone or in combinationwith each other or any of the above courier characteristics, to identifyat least one potential courier.

Scheduling platform 225 may, in some implementations, identify at leastone potential courier for only one of the product locations (e.g., insome situations only one combination of product location and potentialcourier may be capable of fulfilling and delivering a particularproduct). In some implementations, a single potential courier may beidentified as a potential courier for multiple product locations. Forexample, an independent contractor based delivery service may haveindividuals capable of delivering products in a geographic area thatincludes multiple product locations. In this situation, the couriercharacteristics may vary based on the product location from which thecourier will pick up the product (e.g., the cost associated with courierdelivery, traffic associated with courier delivery, and/or insurancecharacteristics might change based on the product location).

In this way, scheduling platform 225 may identify at least one potentialcourier for each of the product locations, providing scheduling platform225 with situational awareness regarding potential couriers that may beavailable to deliver products for one or more of the product locations.Identifying at least one potential courier may further enable schedulingplatform 225 to select a particular product location and particularcourier.

As shown in FIG. 4 , process 400 may include selecting a particularproduct location and a particular courier (block 460). For example,scheduling platform 225 may select a particular product location andparticular courier. In some implementations, scheduling platform 225 mayselect the particular product location and/or the particular courierbased on information obtained from user device 210, product locationdevice(s) 220, courier device(s) 240, and/or third party device(s) 250.For example, scheduling platform 225 may select the particular productlocation and/or the particular courier based on the delivery time, thedelivery location, at least one courier characteristic associated withat least one potential courier, at least one product locationcharacteristic associated with at least one product location, and/ordata provided from a third party device (e.g., traffic information,weather information, or the like). In some implementations, as describedabove, a delivery location and/or a product location may be dynamic(e.g., estimated by scheduling platform 225 and/or periodically updatedby a corresponding user device 210 and/or product location device 220).

In some implementations, scheduling platform 225 may select theparticular product location and/or the particular courier by providinginformation obtained from user device 210, product location device(s)220, courier device(s) 240, and/or third party device(s) 250 to anartificial intelligence model (e.g., a machine learning model) trainedto select a product location and/or a courier based on the obtainedinformation (e.g., delivery location, delivery time, product location,fulfillment time, product location characteristics, couriercharacteristics, or the like). For example, scheduling platform 225 mayprovide, for each of the product locations, a scheduling model with atleast one product location characteristic associated with a productlocation and at least one courier characteristic associated with apotential courier. In this situation, the scheduling model may have beentrained to produce, as output, an estimated completion time associatedwith delivery of the product to the delivery location. In someimplementations, the scheduling model may be trained to produce, asoutput, an estimated cost associated with delivery of the product to thedelivery location.

In some implementations, the scheduling model may be trained to produce,as output, a score that provides a measure with which schedulingplatform 225 may evaluate a particular combination of a particularproduct location and particular courier. For example, the schedulingmodel may produce a score for a combination of product location andpotential courier, the score being based on input data indicatingcourier cost, courier ability to deliver on time, fulfillment timeassociated with the product location, or the like. Scores output fromthe scheduling model may be compared and/or ranked to determine theparticular product location from which the requested product will beprepared and to determine the particular courier that will pick up therequested product from the product location and deliver it to thedelivery location. Other types of machine learning models may be used byscheduling platform 225 to facilitate selection of a particular productlocation and/or a particular courier. In some implementations, selectionmay be automatic (e.g., based on highest ranked machine learning scoresor the like), and in some implementations, selection may be made by auser associated with scheduling platform (e.g., scheduling platform 225may receive input from user selecting the particular product locationand particular courier).

In this way, scheduling platform 225 may select a particular productlocation and particular courier, enabling scheduling platform 225 toperform an action based on the particular product location or theparticular courier.

As shown in FIG. 4 , process 400 may include performing an action basedon the particular product location or the particular courier (block470). For example, scheduling platform 225 may perform an action basedon the particular product location and/or the particular courier. Theactions performed may vary, and in some implementations, multipleactions may be performed. Some example actions are designed tofacilitate timely (e.g., quick and/or within a particular time)fulfillment (e.g., preparation and packaging) and delivery of a productto the delivery location specified by the user.

In some implementations, scheduling platform 225 may provide, to productlocation device 220 associated with the particular product location,data specifying the product, the fulfillment time, and/or the particularcourier. For example, data provided to product location device 220 mayenable product location device 220 (and/or an entity associated withproduct location device 220) to prepare the product within thefulfillment time.

In some implementations, scheduling platform 225 may provide, to courierdevice 240 associated with the particular courier, data specifying theproduct, the fulfillment time, the particular product location, deliverytime, and/or the delivery location. For example, data provided tocourier device 240 may enable courier device 240 (and/or the particularcourier associated with courier device 240) to pick up the product atthe fulfillment time and particular product location, and to deliver theproduct to the delivery location at the delivery time.

In some implementations, scheduling platform 225 may provide, to anotherdevice (e.g., user device 210), data specifying the particular productlocation and/or the particular courier. In some implementations, dataspecifying other information (e.g., in addition to or alternatively tothe particular product location and/or the particular courier) may beprovided to another device. For example, scheduling platform 225 maysend user device 210 a response to the product request, and the responsemay indicate a variety of information related to the product request,such as the particular courier delivering the requested product, thedelivery time, the particular product location, or the like. As anotherexample, scheduling platform 225 may send information, such as a costassociated with the product and/or particular courier, to a paymentprocessor associated with user device 210 (e.g., in a manner designed tocharge or credit a user account associated with user device 210). As yetanother example, various pieces of information may be provided to amachine learning model training device (e.g., in a manner designed toupdate an existing model and/or generate a new model to facilitatescheduling product preparation and delivery).

In some implementations, scheduling platform 225 may perform an actionto determine at least two delivery options. For example, in addition toselecting a particular product location and a particular courier,scheduling platform may select one or more other product locationsand/or one or more other couriers (e.g., based on product locationcharacteristics, courier characteristics, scheduling model results, orthe like). In this situation, each delivery option may be associatedwith one of the product locations and/or at least one potential courier.As an example, scheduling platform 225 may determine the deliveryoptions based on estimated delivery times associated with preparationand delivery of the product to the delivery location from variouscombinations of product location and courier.

In some implementations, scheduling platform 225 may determine deliveryoptions by obtaining third party data from at least one third partydevice and determining the delivery options based on the third partydata. For example, the third party data may include data specifyingweather conditions associated with the geographic region, and/or dataspecifying traffic conditions associated with the geographic region. Insome implementations, scheduling platform 225 may provide an artificialintelligence model (e.g., the scheduling model described above) with atleast a portion of the third party data, (e.g., in a manner designed toobtain a score or other measure which may be used to determine whether acombination of product location and courier is a delivery option).

In some implementations, when determining at least two delivery options,scheduling platform 225 may provide another device (e.g., user device210) with data identifying the delivery options, and may receive, fromthe other device, a selection of one of the delivery options. Forexample, scheduling platform 225 may send, to user device 210, data thatpresents multiple delivery options for the user of user device 210. Theuser of user device 210 may select one of the delivery options via auser interface on user device 210, causing user device 210 to transmitthe selection to scheduling platform 225. In this situation, schedulingplatform 225 may use the selection provided by the user to select theproduct location and courier to prepare and deliver the product.

While a variety of example actions are described above, schedulingplatform 225 may be capable of performing a variety of actions designedto facilitate scheduling preparation and delivery of a product. In thisway, scheduling platform 225 may perform an action based on theparticular product location or the particular courier.

Although FIG. 4 shows example blocks of process 400, in someimplementations, process 400 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 4 . Additionally, or alternatively, two or more of theblocks of process 400 may be performed in parallel.

As a particular example of process 400, scheduling platform 225 mayinclude a platform utilized by a bank that desires to offer quickdelivery of banking products (e.g., credit cards, debit cards, cash,cashier's checks, or the like) that might require some preparation bybanking devices and/or banking personnel. In this situation, a user ofuser device 210 may send a request for a cashier's check to schedulingplatform 225, such as while using a banking application operating onuser device 210. The request may include a geographic location fordelivery (e.g., a home address of the user). Additionally, the user mayrequest delivery of the cashier's check at a particular time, such aswhen the user will be home, or as soon as possible.

Continuing with the example, scheduling platform 225 may identifyproduct locations (e.g., bank branches, ATMs, warehouse locations,storage lockers, or the like) that might have the requested product. Inthis situation, scheduling platform 225 may narrow down the productlocations to product locations that have cashier's checks in stock, andthat have the banking equipment and/or personnel to prepare a cashier'scheck. For example, based on this criteria, scheduling platform 225 maynarrow down the product locations to three nearby bank locations (e.g.,different banks, different branch locations of a same bank, or thelike).

Continuing with the example, scheduling platform 225 may determine afulfillment time for the product locations (e.g., a time that thecashier's check will be ready for pickup by a courier). The fulfillmenttime may depend on how long the cashier's check takes to print, how busythe bank location is, how busy the equipment/personnel used to preparethe cashier's check is, or the like. By way of example, schedulingplatform 225 may use a machine learning model to determine an estimatedfulfillment time based on various product location characteristics.Scheduling platform 225 may then identify multiple potential couriersfor the product locations (e.g., the bank locations), such as a dronedelivery option from one of the bank locations, a courier service foranother one of the bank locations, and a carrier service for another oneof the bank locations.

Continuing with the example, scheduling platform 225 may select one ofthe product locations (e.g., bank locations) and one of the deliveryoptions based on factors such as the fulfillment time, cost of acourier, ability for a courier to meet a delivery time, or the like. Asa specific example, traffic (e.g., a measurement of traffic thatsatisfies a threshold) may disqualify a courier or a bank location, evenin a situation where the disqualified courier is closer to the productlocation and/or delivery location than other couriers. As anotherexample, a drone delivery option may be disqualified based on weatherconditions (e.g., in a situation where visibility does not meet avisibility threshold). Upon selecting a particular product location(e.g., bank location), scheduling platform 225 may perform an action bysending a notification to a courier regarding the fulfillment time,delivery location, and delivery time, sending instructions to a productlocation device at a bank location to initiate preparation of thecashier's check, and sending confirmation data regarding the productdeliver to user device 210 associated with the request. In this way,scheduling platform 225 may use process 400 to schedule preparation anddelivery of a product.

The foregoing disclosure provides illustration and description, but isnot intended to be exhaustive or to limit the implementations to theprecise form disclosed. Modifications and variations are possible inlight of the above disclosure or may be acquired from practice of theimplementations.

As used herein, the term component is intended to be broadly construedas hardware, firmware, or a combination of hardware and software.

Some implementations are described herein in connection with thresholds.As used herein, satisfying a threshold may refer to a value beinggreater than the threshold, more than the threshold, higher than thethreshold, greater than or equal to the threshold, less than thethreshold, fewer than the threshold, lower than the threshold, less thanor equal to the threshold, equal to the threshold, or the like.

It will be apparent that systems and/or methods, described herein, maybe implemented in different forms of hardware, firmware, or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods were described herein without reference tospecific software code—it being understood that software and hardwarecan be designed to implement the systems and/or methods based on thedescription herein.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of possible implementations. In fact,many of these features may be combined in ways not specifically recitedin the claims and/or disclosed in the specification. Although eachdependent claim listed below may directly depend on only one claim, thedisclosure of possible implementations includes each dependent claim incombination with every other claim in the claim set.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. As usedherein, the term “or the like” is intended to be inclusive (e.g., as in“and/or the like”), unless explicitly stated otherwise. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and may be used interchangeably with “one or more.” Furthermore,as used herein, the term “set” is intended to include one or more items(e.g., related items, unrelated items, a combination of related andunrelated items, etc.), and may be used interchangeably with “one ormore.” Where only one item is intended, the term “one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

What is claimed is:
 1. A device, comprising: one or more memories; andone or more processors, communicatively coupled to the one or morememories, to: receive, from a user device via a user interface, arequest for a product; determine, based on geo-location information ofthe user device, a geographic location for delivery of the product;receive information from a proximity detection device to determine atleast one product location characteristic; determine, based on the atleast one product location characteristic, a fulfillment time indicatinga time at which the product will be at a product location and preparedfor delivery; identify, based on determining the fulfillment time, atleast one potential courier; select, based on the fulfillment time, thegeographic location for delivery, and at least one couriercharacteristic associated with the at least one potential courier, aparticular delivery option; provide, to the user device, informationidentifying the particular delivery option; and provide, to a courierdevice associated with the particular delivery option, data identifyingat least one of the product, the fulfillment time, the product location,or the geographic location for delivery.
 2. The device of claim 1,wherein the geo-location information is determined based on an inputassociated with the user device.
 3. The device of claim 1, wherein thegeographic location for delivery is dynamically updated.
 4. The deviceof claim 1, wherein the one or more processors are further to: provide,to the user device, a notification to confirm the geographic locationfor delivery.
 5. The device of claim 1, wherein the information from theproximity detection device comprises: information indicating that awearable device is within a threshold range of the proximity detectiondevice.
 6. The device of claim 1, wherein the one or more processors,when determining the fulfillment time, are configured to: determine thefulfillment time based on a previous fulfillment time associated with atleast one of the product location or the at least one product locationcharacteristic.
 7. The device of claim 1, wherein the at least oneproduct location characteristic comprises one or more of: dataindicating which products are in stock at the product location, dataindicating which entities are capable of preparing the products, orschedules for the entities.
 8. A method, comprising: receiving, by adevice, a request for a product; determining, by the device and based ongeo-location information, a geographic location for delivery of theproduct; receiving, by the device, information from a proximitydetection device to determine at least one product locationcharacteristic; determining, by the device and based on the at least oneproduct location characteristic, a fulfillment time indicating a time atwhich the product will be at a product location and prepared fordelivery; identifying, by the device and based on determining thefulfillment time, at least one potential courier; selecting, by thedevice and based on the fulfillment time, the geographic location fordelivery, and at least one courier characteristic associated with the atleast one potential courier, a particular delivery option; andproviding, by the device and to a courier device associated with theparticular delivery option, data identifying at least one of theproduct, the fulfillment time, the product location, or the geographiclocation for delivery.
 9. The method of claim 8, wherein determining thefulfillment time comprises: determining the fulfillment time based on apredetermined fulfillment time associated with at least one of theproduct location or the at least one product location characteristic.10. The method of claim 8, wherein determining the fulfillment timecomprises: determining, using a machine learning model, the fulfillmenttime.
 11. The method of claim 8, wherein identifying the at least onepotential courier comprises: identifying, based on obtaining couriercharacteristic information, the at least one potential courier.
 12. Themethod of claim 8, wherein the information identifying the particulardelivery option identifies the product location and a particular courierof the at least one potential courier.
 13. The method of claim 8,wherein selecting the particular delivery option comprises: selectingthe particular delivery option based on data provided from a third partydevice.
 14. The method of claim 8, further comprising: providinginformation regarding the fulfillment time, the geographic location fordelivery, and the at least one courier characteristic to an artificialintelligence model; and wherein selecting the particular delivery optioncomprises: selecting the particular delivery option based on providingthe information regarding the fulfillment time, the geographic locationfor delivery, and the at least one courier characteristic to theartificial intelligence model.
 15. A non-transitory computer-readablemedium storing a set of instructions, the set of instructionscomprising: one or more instructions that, when executed by one or moreprocessors of a device, cause the device to: determine, based ongeo-location information, a geographic location for delivery of aproduct; receive information from a proximity detection device todetermine at least one product location characteristic; determine, basedon the at least one product location characteristic, a fulfillment timeindicating a time at which the product will be at a product location andprepared for delivery; identify, based on determining the fulfillmenttime, at least one potential courier; select, based on the fulfillmenttime, the geographic location for delivery, and at least one couriercharacteristic associated with the at least one potential courier, aparticular delivery option; and provide, to a courier device associatedwith the particular delivery option, data identifying at least one ofthe product, the fulfillment time, the product location, or thegeographic location for delivery.
 16. The non-transitorycomputer-readable medium of claim 15, wherein the one or moreinstructions further cause the device to: provide information regardingthe fulfillment time, the geographic location for delivery, and the atleast one courier characteristic to a scheduling model; and receive,from the scheduling model, one or more scores associated with one ormore delivery options; and wherein the one or more instructions, thatcause the device to select the particular delivery option, further causethe device to: select the particular delivery option based on the one ormore scores.
 17. The non-transitory computer-readable medium of claim15, wherein the one or more instructions further cause the device to:provide information regarding the selection of the particular deliveryoption to a machine learning model training device.
 18. Thenon-transitory computer-readable medium of claim 15, wherein the one ormore instructions further cause the device to: select the particulardelivery option based on data provided from a third party device. 19.The non-transitory computer-readable medium of claim 15, wherein the oneor more instructions further cause the device to: periodically receivean updated geographic location for delivery; and wherein the one or moreinstructions, that cause the device to select the particular deliveryoption, further cause the device to: select the particular deliveryoption based on the updated geographic location for delivery.
 20. Thenon-transitory computer-readable medium of claim 15, wherein the one ormore instructions further cause the device to: receive, from a userdevice, a request for the product; and receive information regarding aspeed and direction of travel associated with the user device; andwherein the one or more instructions, that cause the device to determinethe geographic location for delivery of the product, further cause thedevice to: determine the geographic location for delivery of the productbased on the information regarding the speed and direction of travelassociated with the user device.